First Nations Food Environments: Exploring the Role of Place, Income, and Social Connection
Bibliographic record
Abstract
BACKGROUND: In Canada, few studies have examined how place shapes Indigenous food environments, particularly among Indigenous people living in southern regions of Ontario. OBJECTIVE: This paper examines and compares circumstances of food insecurity that impact food access and dietary quality between reserve-based and urban-based Indigenous peoples in southwestern Ontario. METHODS: = 99) contexts in southwestern Ontario. RESULTS: Rates of food insecurity are high in both geographies (55% and 35% among urban- and reserve-based respondents, respectively). Urban-based participants were 6 times more likely than those living on-reserve to report 3 different measures of food insecurity. Urban respondents reported income to be a significant barrier to food access, while for reserve-based respondents, time was the most pressing barrier. Compared with recommendations from Canada's Food Guide, our data revealed overwhelming trends of insufficient consumption in 3 food categories among all respondents. Close to half (54% and 52%) of the urban- and reserve-based samples reported that they eat traditional foods at least once a week, and respondents from both groups (76% of urban- and 52% of reserve-based respondents) expressed interest in consuming traditional foods more often. CONCLUSIONS: Indigenous Food Sovereignty and community-led research are key pathways to acknowledge and remedy Indigenous food insecurity. Policies, social movements, and research agendas that aim to improve Indigenous food security must be governed and defined by Indigenous people themselves. Indigenous food environments constitute political, social, and cultural dimensions that are infinitely place based.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".